Designing an ideal anticancer molecule

Hypotheses

  1. Since cancer cells are different from normal cells in many aspects, there exists a well-defined molecular mechanism differentiating cancer (immortal) cells from adult (differentiated, mortal) cells. We will call it Cancer-Specific Molecular Machinery (CSMM). By definition, CSMM is common for many (perhaps, all) types of cancer.

  2. CSMM is present not only in tumor cells and cancer cell lines, but also in cancer stem cells, and it different from the pluripotency machinery in “normal” stem cells.

  3. CSMM can be targeted by small molecule drugs. In other words, it is possible to find a small molecule that will be toxic for most/all cancer cells and much less toxic for normal cells.

  4. Among the >100,000 molecules NCI has already tested on the NCI-60 cell panel, some of the molecules are already targeting CSMM, albeit inefficiently.

  5. By bioinformatic analysis of NCI-60 datasets, it is possible to identify a group of molecules enriched with the CSMM-targeting molecules. We will call this group CSMM-targeting candidates.

  6. Based on the identified CSMM-targeting candidates and NCI-60 data, it is possible to build empirical models of CSMM-targeting molecules with sufficient predictive power for meaningful prediction of their Efficacy E, Unspecificity U and Safety S.

  7. Based on the above predictions for millions of molecules generated in silico based on the best CSMM-targeting candidates, it is possible to identify most promising candidates.

Aims

  1. To predict novel small molecule candidates which should be:
    • active (in terms of \(IC_{50}/LC_{50}\)),
    • unspecific (similar \(IC_{50}/LC_{50}\) across different cancer cell lines),
    • safe (non-toxic).

  2. Synthesize these candidate molecules and test their activity and unspecificity on cell panels, including the NCI-60 panel.

  3. Provided E and U are high, find the protein targets and mechanism(s) of action of these molecules using the FITExP method (expression-based analysis).

  4. Confirm the protein targets of these molecules using the SITExP method (solubility-based analysis).

  5. Based on these results, test the hypothesis 1.

  6. Determine the toxicity of the candidate molecules on normal stem cells, thus testing the hypothesis 2.

  7. Provided the targets and the mechanisms are novel and look like a plausible CSMM candidate, determine experimentally the safety S of the novel molecules, thus testing the hypotheses 3-7.

Methods

  1. “Seed” selection (ACh).

    1. DTP-NC60 dataset will be used as a starting point for candidate molecule identification. There are more than 100,000 small molecules tested, ~33,000 has measured IC50 values in at least 50 of 60 cell lines. For each of the compound in dataset we will calculate following characteristics:
      • Efficacy E, as \(-log(IC_{50})\) averaged over cell lines.
      • Unspecificty U, difference between the max and mean \(-log(IC_{50})\).
      • Safety S, using GUSAR’s Acute Mice Toxicity model.
    2. We will define the figure-of-merit function Q(E,U,S) assingns then highest value to the ”best” molecules.
    3. Then we will select 500-1000 best candidates with the highest Q values.

  2. Clustering by MOA (ACh).

    For each of the selected candidate molecules, an activity spectrum (AS) will be calculated using PASS software. Then the molecules will be clustered by similarity (correlation or covariation) of AS. One or two most consistent and large clusters will be selected (expected to comprise 20-50 molecules each).

  3. Cluster enrichment and candidate selection (ACh).

    1. Each of the selected clusters will be enriched by structurally similar molecules from the DTP-NC60 dataset.
    2. For each of the selected clusters, we will build, using PASS and GUSAR, models predicting E and U. Toxicity model already exists (GUSAR).
    3. For each cluster, we will select molecules from the Chembl database that pass the structural similarity threshold (will be defined for each cluster).
    4. For thus selected molecules E, U and S will be calculated, as well as Q.
    5. Best hits (max Q) will be selected in each cluster. Based on their structural features and AS, it will be analyzed whether they represent essentially the same structure or different structures. In the first case, simplest structure will be chosen as “seed”. In the latter case, several different simplest structures will be chosen as seeds.

  4. Experimental validation (AS).

    The seeds from each cluster will be ordered (or synthesized) and tested in the lab on at least three different cancer cell lines (HCT116, RKO and A375(?)). Experimental IC50 values will be determined. All hits found to be active will be sent to NCI-60 for testing on 60 cell lines.

  5. Targets and MOA identification (AS and ACh).

    FITExP and SITExP methods will be used to identify the targets and MOA of the verified hits.

  6. Novel target validation (AS).

    Novel target candidates identified by UTIExP will be validated using siRNA.

  7. Safety of novel molecules (AS; outsourced).

    Determine the toxicity of the candidate molecules on normal stem cells. Safety of novel molecules for animals will be tested by commercial labs.

1. Seed selection

Preparing environment

In [1]: 
# For inline graphics
%pylab inline
from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw
Draw.DrawingOptions.elemDict[0]=(0.,0.,0.)  # draw dummy atoms in black
from rdkit.Chem import PandasTools
from rdkit.Chem import AllChem as Chem
from rdkit.Chem import DataStructs

# Pandas and Numpy - musthave
import pandas as pd
import numpy as np
%config InlineBackend.figure_format='retina'
# Love this!
import mpld3
mpld3.enable_notebook()

from IPython.display import display
from IPython.display import display_pretty, display_html, HTML, Javascript, Image

pd.options.display.mpl_style = 'default'
pd.options.display.float_format = '{:.2f}'.format
rcParams['figure.figsize'] = 12,9
import warnings
warnings.filterwarnings('ignore')

HTML('''<script>
code_show=true; 
function code_toggle() {
 if (code_show){
 $('div.input').hide();
 } else {
 $('div.input').show();
 }
 code_show = !code_show
} 
$( document ).ready(code_toggle);
</script>
The raw code for this IPython notebook is by default hidden for easier reading.
To toggle on/off the raw code, click <a href="javascript:code_toggle()">here</a>.''')

Populating the interactive namespace from numpy and matplotlib
Out[1]:
The raw code for this IPython notebook is by default hidden for easier reading. To toggle on/off the raw code, click here.

Load NCI60 data (structures and activities)

In [2]: 
gi50 = pd.read_table('/Volumes/public/Users/Alexey/DrugDiscovery/NCI60/DTP_NCI60_RAW.txt', skiprows=7, sep='\t', na_values='-')
not_cells = [x for x in gi50.columns if ':' not in x]
cells = [x for x in gi50.columns if ':' in x]
smiles = pd.read_table('/Volumes/public/Users/Alexey/DrugDiscovery/NCI60/NCIOPENB_SMI', sep='\s+', header=None, index_col=0, names=['hz','smiles'])

print("{0} records from DTP_NCI60 were loaded. {1} structures were loaded from SMILES file".format(len(gi50.index), len(smiles)))

73841 records from DTP_NCI60 were loaded. 237771 structures were loaded from SMILES file

Averaging

Loaded data from DTP_NCI60 may contain multiple records for single compounds. Thus, we will take median GI50 value for each compound in each cell line

In [3]: 
data_melted = pd.melt(gi50, id_vars=not_cells)
data_pivot = pd.pivot_table(data_melted, values='value', index='NSC #',columns='variable', aggfunc=np.median)
print("Data for {0} compounds was loaded".format(len(data_pivot)))

Data for 49847 compounds was loaded
In [4]: 
HTML(data_pivot.iloc[:5,:10].to_html())
Out[4]:
variable BR:BT_549 BR:HS578T BR:MCF7 BR:MDA_MB_231 BR:T47D CNS:SF_268 CNS:SF_295 CNS:SF_539 CNS:SNB_19 CNS:SNB_75
NSC #
1 4.81 4.75 4.83 4.79 5.60 4.78 4.63 4.77 4.05 4.94
17 6.47 4.60 4.73 4.51 6.37 5.75 5.73 6.11 4.00 4.97
26 nan nan 4.97 5.36 4.85 5.36 5.70 5.44 4.84 5.77
89 nan nan nan nan nan 4.00 4.00 4.00 4.00 4.00
171 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00

Filtering for sufficient number of measurements

We will keep only compounds with GI50 values in at least 40 of 60 cell lines

In [5]: 
nans = data_pivot.apply(lambda x: sum(isnan(x)), axis=1)
gi50_ok = data_pivot[nans<20]
print("{0} compounds left for further analysis".format(len(gi50_ok)))

48758 compounds left for further analysis

GI50 distribution properties for each compound

In [6]: 
from scipy import stats
gi50_ok['NSC #'] = gi50_ok.index
data_melted = pd.melt(gi50_ok, id_vars='NSC #')
grouped = data_melted.groupby('NSC #')
def skew(x):
    return stats.skew(x.dropna(), bias=True)
def kurtosis(x):
    return stats.skew(x.dropna(), bias=True)

data_averaged = grouped['value'].agg({
    'mean': lambda x: mean(x.dropna()),
    'median': lambda x: median(x.dropna()),
    'min': lambda x: np.min(x.dropna()),
    'max': lambda x: np.max(x.dropna()),
    'skew': lambda x: stats.skew(x.dropna(), bias=True),
    'sd' : lambda x: np.std(x.dropna()),
    'dif_from_median' : lambda x: sum(abs(x.dropna()-median(x.dropna()))>0.001),
    'kurtosis': lambda x: stats.kurtosis(x.dropna(), fisher=True, bias=True)})
data_averaged['cv'] = data_averaged['sd'] / data_averaged['mean']
HTML(data_averaged.head().to_html())
Out[6]:
min kurtosis max skew sd median dif_from_median mean cv
NSC #
1 4.05 0.08 5.70 0.82 0.35 4.79 58.00 4.89 0.07
17 4.00 -0.96 7.30 0.64 1.00 4.73 58.00 4.93 0.20
26 4.83 -1.40 5.78 -0.16 0.32 5.38 52.00 5.32 0.06
89 4.00 2.40 5.82 1.25 0.38 4.33 50.00 4.34 0.09
171 4.00 -3.00 4.00 0.00 0.00 4.00 0.00 4.00 0.00

Further data filtering

We will require at least 20 values over 60 cell lines to be different from median value (If many values are equal to median value it usually means only one concentration was measured).

In [7]: 
data_diff = data_averaged[(data_averaged['dif_from_median']>20) & (data_averaged['cv'] < 1.0) & (data_averaged['cv']>0)]
print("{0} compounds left for further analysis".format(len(data_diff)))

27168 compounds left for further analysis

Dataset overview in terms of GI50 values distribution

We have to subset our dataset in terms of - unspecificty U, - efficacy E.

To assess unspecificity of compounds, we will consider CV (standard deviation divided my the mean value):

In [8]: 
#matplotlib.rc('text', usetex=False)
#matplotlib.rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"]
density = stats.gaussian_kde(data_diff['cv'])
xx = np.linspace(0, 0.2, 300)
plot(xx, density(xx), lw=2)
fill_between(xx, density(xx),0, alpha=0.2)
xlim([0.,0.3])
data_diff['cv'].hist(bins=200, normed=True)
xlabel(r'CV')
Out[8]:
<matplotlib.text.Text at 0x1197d8bd0>

To assess efficacy E we will consider -log(GI50) values distribution:

In [10]: 
density = stats.gaussian_kde(data_diff['mean'])
xx = np.linspace(data_diff['mean'].min(), data_diff['mean'].max(), 300)
plot(xx, density(xx), lw=2)
fill_between(xx, density(xx),0, alpha=0.2)
data_diff['mean'].hist(bins=50, normed=True)
xlabel('Mean -log10(GI50)')
Out[10]:
<matplotlib.text.Text at 0x119aa69d0>

And scatterplot - CV vs mean -log10(GI50) (some points omitted):

In [12]: 
data_5 = data_diff.iloc[::15,:]
scatter(data_5['mean'], data_5['cv'])
xlabel('Mean -log10(GI50)')
ylabel('CV')
Out[12]:
<matplotlib.text.Text at 0x11a9e0410>

Shortlist generation

Instead of figure of merit function S i would suggest to use figure of merit rules:

  • high efficacy – \(mean(-log10(GI_{50}) > 6\);
  • low specificity – \(CV(-log10(GI_{50}) < 5\%\);
  • toxicity will be calculated later.
In [29]: 
data_seeds = data_diff[(data_diff['mean']>6) & (data_diff['cv'] < 0.05)]
print('{0} compounds selected'.format(len(data_seeds)))

512 compounds selected
In [31]: 
suppl = Chem.SDMolSupplier('/Users/black/Google Drive/NCI60-drugs/March2012_2d_dos.sdf')
compounds = {}
for mol in suppl:
    if mol:
        nnsc = int(mol.GetProp('NSC'))
        compounds[nnsc] = mol
In [47]: 
data_seeds = data_diff[(data_diff['mean']>6) & (data_diff['cv'] < 0.05)]
print('{0} compounds selected'.format(len(data_seeds)))
data_seeds['Mol'] = [(x in compounds) and compounds[x] or '' for x in data_seeds.index]
data_seeds = data_seeds[data_seeds.Mol != '']
print('For {0} compounds molecular structure found'.format(len(data_seeds)))
#PandasTools.AddMoleculeColumnToFrame(data_seeds, smilesCol='smiles', molCol='Mol')
HTML(data_seeds.sort('mean', ascending=False).head().to_html())

512 compounds selected
For 450 compounds molecular structure found
Out[47]:
min kurtosis max skew sd median dif_from_median mean cv Mol
NSC #
670038 10.00 -0.18 11.47 0.23 0.35 10.61 56.00 10.63 0.03 Mol
693565 9.26 1.99 10.60 -1.36 0.30 10.35 60.00 10.33 0.03 Mol
357704 9.42 -0.32 10.73 -0.21 0.27 10.07 60.00 10.02 0.03 Mol
707389 8.34 1.33 10.05 -1.15 0.38 9.60 58.00 9.57 0.04 Mol
611747 7.00 17.43 9.94 -3.73 0.44 9.73 56.00 9.56 0.05 Mol
In [39]: 
pass_input = '/Volumes/public/Users/Alexey/DrugDiscovery/NCI60/20141219_magicbullet_forpass.sdf'
writer = Chem.SDWriter(pass_input)
for idx,row in data_seeds.sort('mean', ascending=False).iterrows():
    mol = row['Mol']
    mol.SetProp('gi50_mean',"%.4f"%row['mean'])
    mol.SetProp('gi50_cv',"%.4f"%row['cv'])
    mol.SetProp('gi50_max',"%.4f"%row['max'])
    mol.SetProp('gi50_median',"%.4f"%row['median'])
    writer.write(mol)
writer.close()
In [45]: 
pass_output = pass_input.replace('.sdf', ' (PASS2A).CSV')
pass_result = pd.read_csv(pass_output, skiprows=8, index_col=0)
In [46]: 
print("For {0} molecules PASS predictions were obtained".format(len(pass_result)))

For 385 molecules PASS predictions were obtained
In [48]: 
effects = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-1-E  Effects.txt").readlines()]
mechanisms = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-2-M  Mechanisms.txt").readlines()]
toxicity = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-4-T  Toxicity.txt").readlines()]
metabolism = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-16-Z Metabolism.txt").readlines()]
transport = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-64-C Transport.txt").readlines()]

pass_toxic = pass_result[[a for a in toxicity if 'Toxic' in a or 'toxic' in a]]
In [81]: 
from sklearn import decomposition, preprocessing
pass_mechanisms = pass_result[mechanisms]
pass_mechanisms_scaled = preprocessing.scale(pass_mechanisms)
pca = decomposition.PCA()
pca.fit(pass_mechanisms_scaled)
Out[81]:
PCA(copy=True, n_components=None, whiten=False)
In [82]: 
X = pca.transform(pass_mechanisms)

MOA Clustering

Selected compounds were subjected for PCA analysis. Each compound was characterised by a vector of PASS activities (Mechanisms section) with at least 20 non-negative values over all selected compounds.

Summary of PCA analysis:

  • PC1 explained 44.1% of variance;
  • PC2 explained 11.6% of variance;
  • 25 PCs explained 90% of variance;
  • 49 PCs explaned 95% of variance.

Results of PCA analysis were subjected to agglomerative hierarchical clustering procedure. 8 clusters were generated.

In [89]: 
Image('PCAclusters.png', width=600)
Out[89]:
In [94]: 
clusters = pd.read_csv('clusters2/clustered.csv', index_col=0)
clusters_grouped = clusters.groupby('clust')
In [159]: 
htmlall = ''
nsc_info = gi50[[u'Drug name', u'FDA Status', u'Mechanism of Action']]
nsc_info.index = gi50[u'NSC #']
nsc_info.drop_duplicates(inplace=True)
nsc_info.fillna('', inplace=True)
for num, dd in clusters_grouped.groups.items():
    clusterdata_1 = data_seeds.ix[dd,['median','cv','min','max','Mol']]
    clusterdata_1 = pd.merge(clusterdata_1, pass_toxic[['Cytotoxic','Embryotoxic']], left_index=True, right_index=True, how='left')
    clusterdata_1 = pd.merge(clusterdata_1, nsc_info, left_index=True, right_index=True)
    htmlall += "<h3>Cluster {0}</h3>".format(num)+clusterdata_1.to_html() + "<br/>"
In [160]: 
HTML(htmlall)
Out[160]:

Cluster 1

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
611747 9.73 0.05 7.00 9.94 Mol 3.11 -2.02 Calyculin A
671677 8.30 0.03 7.51 8.30 Mol 11.39 -0.70 Sphinxolide B
671678 7.40 0.04 6.46 8.23 Mol 11.16 -0.84 Sphinxolide C Unknown
671680 6.93 0.04 6.43 7.84 Mol 11.07 -0.86 Sphinxolide Unknown
702923 7.27 0.05 6.39 8.15 Mol 8.62 -0.69 sphinxolide E
702924 8.20 0.04 7.60 9.28 Mol 12.34 -1.04 sphinxolide F
722656 6.53 0.02 6.22 6.86 Mol 4.58 -0.03 Partricin A morpholide

Cluster 2

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
665803 8.65 0.05 6.96 9.00 Mol 2.74 -2.53 15H-Pyrrolo[2,1-f][1,15,4,7,10,20] dioxatetraazacyclotricosine-1,4,8,13,16,18,21-heptaone, docosahydro-11-hydroxy-3-[(4-methoxyphenyl)methyl]- 2,6,17-trimethyl-15-(methylethyl)-10-(1-methylpropyl)- 2
682345 7.75 0.03 6.50 7.96 Mol 0.15 -2.87 Aurantimycin B Unknown
712199 8.42 0.03 7.11 8.60 Mol 3.15 -2.72 Didemnin B aminomethylene
714370 8.33 0.05 6.65 9.00 Mol 2.22 -2.65 dehydrotamandarin-A

Cluster 3

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
21205 8.39 0.02 7.82 8.43 Mol 1.36 -1.14 Pluramycin A Unknown
42076 6.44 0.04 5.34 6.65 Mol 1.71 0.13 .beta.-D-Glucopyranoside, 5,5a,6,8,8a,9-hexahydro-6-oxo-5-(3,4,5-trimethoxyphenyl)furo[3',4':6,7]naphtho[2,3-d]-1,3-dioxol-9-yl, [5R-(5.alpha.,5a.beta.,8a.alpha.,9.alpha.)]-
70929 9.20 0.05 8.60 10.50 Mol 1.42 -1.28 Antibiotic B26,158 Unknown
102815 6.50 0.04 5.68 7.15 Mol 0.89 -0.20 Compound D from Nogalamycin
114781 8.28 0.03 6.89 8.89 Mol 4.84 -1.07 Pederin
136044 7.49 0.03 6.84 7.88 Mol 1.63 0.26 Rhodomycin A
159628 6.68 0.05 6.06 7.49 Mol 0.26 -0.85 (8,8'-Bi-1H-naphtho[2,3-c]pyran)-3,3'-diacetic acid, 3,3',4,4'-tetrahydro-9,9',10,10'-tetrahydroxy-7,7'-dimethoxy-1,1'-dioxo-, dimethyl ester
243023 8.12 0.03 7.78 9.43 Mol 2.23 0.41 Cinerubin B hydrochloride
261045 7.92 0.04 7.00 8.00 Mol 2.28 0.80 N,N-Dimethyladriamycin Unknown
267229 7.34 0.05 6.50 7.76 Mol 1.59 0.54 Pyrromycin
267469 7.62 0.05 5.54 8.18 Mol 2.22 0.72 Esorubicin T2
268239 7.29 0.04 6.52 7.83 Mol 2.28 0.70 5,12-Naphthacenedione, 7,8,9,10-tetrahydro-6,8,11-trihydroxy-8-(hydroxyacetyl)-1-methoxy-10-[[2,3,6-trideoxy-3-(diethylamino)-.alpha.-L-lyxo-hexopyranosyl]oxy]-, hydrochloride, (8S-cis)- Unknown
269146 8.00 0.05 6.23 8.00 Mol 1.33 2.05 Antibiotic 6604-9A
269754 7.76 0.04 6.31 9.00 Mol 5.38 -0.49 BACCHARIS PRINCIPLE B-2 (B800157F248 AND K381)
328167 8.25 0.03 7.21 8.30 Mol 4.90 -0.59 RORIDIN A, HYDROXY-, 8B-
357704 10.07 0.03 9.42 10.73 Mol 2.06 -0.15 5,12-Naphthacenedione, 10-[[3-(3-cyano-4-morpholinyl)-2,3,6-trideoxy-.alpha.- L-lyxo-hexopyranosyl]oxy]-7,8,9,10-tetrahydro-6,8,11- trihydroxy-8-(hydroxyacetyl)-1-methoxy-, (8S-cis)- Db
603724 8.75 0.02 7.93 9.00 Mol 7.59 -0.36 Roritoxin B from m. roridum
609394 9.08 0.05 8.00 9.83 Mol 5.24 -0.70 B7722121F049(=K053)
626171 6.09 0.04 5.56 6.95 Mol 5.17 -1.24 7,17,18-Trimethoxy mycalamide A
639655 8.05 0.05 7.44 9.00 Mol 1.78 -0.34 3'-Deamino-3'-(4-morpholinyl)-13-dihydro-adriamycin hydrocholoride dihydrate Unknown
641318 9.31 0.05 7.32 10.00 Mol 2.25 0.76 5,12-Naphthacenedione, 10-[[3-[[4,4-di(acetyloxy)butyl]amino]- 2,3,6-trideoxy-.alpha.-L-lyxohexopyranosyl]oxy]- 7,8,9,10-tetrahydro-6,8,11-trihydroxy- 8-(hydroxyacetyl)-1-methoxy-, hydrochloride
641319 8.66 0.03 8.25 9.47 Mol 2.25 0.75 5,12-Naphthacenedione, 10-[[3-[[5,5-di(acetyloxy)pentyl]amino]- 2,3,6-trideoxy-.alpha.-L-lyxohexopyranosyl]oxy]- 7,8,9,10-tetrahydro-6,8,11-trihydroxy- 8-(hydroxyacetyl)-1-methoxy-, hydrochloride
663567 6.38 0.05 5.37 6.73 Mol 0.72 3.54 15-tert-butyl-20-deoxyvinblastine Unknown
670121 8.12 0.03 7.53 8.79 Mol 1.71 1.04 11-Hydroxy aclacinomycin A
670122 8.06 0.04 6.52 8.98 Mol 1.50 0.46 11-Hydroxy aclacinomycin X
693702 6.00 0.05 5.52 6.69 Mol 2.10 -1.24 Gambogic acid
702208 6.03 0.04 5.29 6.62 Mol 1.49 -0.35 Heliquinomycin
708496 6.40 0.03 5.86 7.29 Mol 0.32 -0.90 1-O-(3-O-.beta.-D-glucopyranosylbutyryl)pancratistatin
750154 7.43 0.03 6.78 8.04 Mol 2.74 -1.12 salarin C

Cluster 4

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
7529 7.60 0.03 6.77 8.00 Mol 1.72 0.97 Digitoxin
7533 7.33 0.05 6.43 7.86 Mol 2.31 1.56 Allocor
7534 7.43 0.03 7.01 8.25 Mol 1.56 0.11 SCILLIROSIDIN, GLYCOSIDE
25485 8.00 0.03 6.89 8.00 Mol 1.76 0.95 g-Strophanthin
93134 7.62 0.03 7.43 8.23 Mol 2.26 0.26 Bufa-20,22-dienolide, 3-[(6-deoxy-4-O-.beta.-D-glucopyranosyl-.alpha.-L-mannopyranosyl)oxy]-5,14-dihydroxy-19-oxo-, (3.beta.,5.beta.)- (9CI)
94743 6.52 0.04 6.00 7.42 Mol 2.59 -0.29 Cucurbitacin A
95100 7.38 0.04 6.69 7.73 Mol 1.70 1.17 Digoxin FDA approved
106399 7.48 0.05 6.02 7.78 Mol 3.14 -0.46 .alpha.-Elaterin
112167 6.77 0.02 6.22 7.00 Mol 2.76 -0.57 Cucurbitacine (i)
114340 7.14 0.05 6.36 7.81 Mol 1.13 -0.02 Cochliobolin A
117180 7.27 0.03 6.82 7.60 Mol 1.92 0.08 Scillirosidin, 1.alpha.,2.alpha.-epoxy-
135036 7.30 0.03 7.13 8.45 Mol 1.39 0.14 SCILLIGLAUCOSIDIN
135073 6.42 0.04 5.92 6.78 Mol 2.12 -0.08 WITHACNISTIN
135077 6.69 0.05 6.24 7.50 Mol 1.39 -0.78 BERSALDEGENIN 1,3,5-ORTHOACETATE
138780 8.10 0.02 7.69 8.34 Mol 2.39 2.17 Fusariotoxin T 2
143925 7.57 0.04 6.65 7.87 Mol 1.78 0.73 Calotropin (6CI, 7CI, 8CI) Unknown
163062 7.95 0.04 6.99 8.59 Mol 1.02 -0.22 Triptolid Unknown
177378 7.78 0.02 7.26 8.00 Mol 2.17 2.13 Anguidine
179176 6.49 0.04 5.75 6.78 Mol 0.54 0.03 1-Phenanthrenecarboxylic acid, tetradecahydro-2,9-dihydroxy-1,4a,8-trimethyl-7-[2-[2-(methylamino)ethoxy]-2-oxoethylidene]-10-oxo-, methyl ester, hydrochloride, [1R-(1.alpha.,2.alpha.,4a.alpha.,4b.be
179180 7.70 0.02 7.22 8.00 Mol 0.57 0.41 Norcassamide, hydrochloride
238181 7.56 0.04 6.04 7.95 Mol 0.66 -0.54 Isobrucein B
266494 8.00 0.04 6.77 8.00 Mol 0.95 -0.54 Simalikalactone D
278571 7.69 0.04 6.82 8.00 Mol 2.47 2.10 Ht-2 toxin
291312 8.86 0.05 6.87 9.00 Mol 4.01 -0.34 VERRUCARIN A, 8-HYDROXY Unknown
650471 7.78 0.04 7.18 8.30 Mol 2.22 0.29 Calotropin
682561 6.57 0.05 6.03 7.21 Mol 1.73 0.51 Cardenolide 2 Unknown
688285 7.75 0.04 6.66 8.00 Mol 2.24 0.10 7,8-Dehydrocalotropin Unknown
707148 8.27 0.04 7.10 8.60 Mol 1.75 0.78 Odoroside H
713200 7.54 0.04 6.73 8.00 Mol 0.08 -0.27 Bardoxolone Methyl
714608 6.22 0.03 5.45 6.40 Mol 2.18 1.30 Weltonin
727038 7.88 0.03 6.95 8.00 Mol -0.36 -0.86 CDDO-Im
747712 7.61 0.03 6.65 8.00 Mol 0.57 -0.69 18-benzoyloxy-19-benzoylfuranotriptolide
751641 7.72 0.03 6.89 8.00 Mol 0.75 -0.61 Triptolide 14-tert-butyl carbonate, tert-Butyl (3bS,4aS,5aR,6R,6aS,7aS,7bS,8aS,8bS)-6a-iso-propyl-8b-methyl-1-oxo-1,3,3b,4,4a,6,6a,7a,7b,8b,9,10-dodecahydrotrisoxireno[4b,5:6,7:8a,9]phenanthro[1,2-c]
751642 7.66 0.04 6.54 8.00 Mol 0.81 -0.37 Triptolide N,N-dimethylacetate, (3bS,4aS,5aR,6R,6aS,7aS,7bS,8aS,8bS)-6a-isopropyl-8b-methyl-1-oxo-1,3,3b,4,4a,6,6a,7a,7b,8b,9,10-dodecahydrotrisoxireno[4b,5:6,7:8a,9]phenanthro[1,2-c]furan-6-yl N,N-d

Cluster 5

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
17257 6.25 0.05 5.39 7.11 Mol 0.01 0.12 Acti-dione benzoylacetate
32743 7.92 0.03 7.06 8.38 Mol 0.61 0.98 Acetoxycycloheximide
39147 7.42 0.04 6.63 8.00 Mol 0.42 0.75 Glutarimide, 3-[2-hydroxy-2-(5-hydroxy-3,5-dimethyl-2-oxocyclohexyl)ethyl]-,(-)- (8CI) Unknown
45383 8.00 0.03 6.89 8.32 Mol -0.05 0.82 A 050165L302
52141 6.47 0.05 5.66 7.14 Mol 2.20 -0.17 A 4426 Unknown
52947 8.50 0.04 7.87 9.00 Mol -0.04 -0.95 A 80856F30
56310 7.74 0.03 7.11 8.00 Mol 1.84 0.18 Antibiotic from Penicillium cyaneum Unknown
65380 6.86 0.04 6.45 7.50 Mol 0.27 -0.44 Anthrone, 4a.alpha.,9a.alpha.-epoxy-3.beta.-(2,3-epoxybutyryl)-1,2,3,4,4a,9a.alpha.-hexahydro-1.alpha.,3,4.alpha.,10.alpha.-tetrahydroxy-5-methoxy-2.beta.-methyl- (8CI) Unknown
73846 6.49 0.03 5.70 6.81 Mol 2.02 1.36 Trichodermin
83950 8.00 0.03 8.00 8.89 Mol -0.05 0.82 Streptonigrin Unknown
89671 7.42 0.04 6.70 8.00 Mol 1.84 0.18 (+)-Brefeldin A
99154 6.80 0.01 6.61 7.21 Mol -0.42 2.32 TRIBUTYLTIN PROPIONATE
99171 6.82 0.01 6.64 7.15 Mol -0.29 2.30 TRIBUTYLTIN UNDECYLENATE
99182 6.84 0.02 6.63 7.28 Mol -0.40 2.23 TRIBUTYLTIN STEARATE
106408 7.62 0.03 6.68 8.00 Mol -0.23 -1.31 Anthramycin methyl ether
117175 6.83 0.01 6.67 7.11 Mol -0.65 2.04 TRIBUTYLTIN 2,4-DICHLOROBENZOATE
123111 7.81 0.05 6.77 8.00 Mol 0.61 -0.97 Azirino[2',3':3,4]pyrrolo[1,2-a]indole-4,7-dione, 1,1a,2,8b-tetrahydro-8-(hydroxymethyl)-6-methoxy-1,5-dimethyl-, carbamate (ester)
138425 6.54 0.04 5.97 7.27 Mol 0.87 -0.35 Kinamycin C
216128 7.85 0.04 6.88 8.00 Mol 2.19 -0.60 Borrelidin
267033 6.50 0.03 5.70 7.17 Mol 2.02 1.36 Trichothec-9-en-4-ol, 12,13-epoxy-, acetate, (4.beta.)- (9CI)
269142 6.64 0.03 5.63 6.98 Mol 2.18 1.98 ANGUIDINE DERIV SCIRPENTRIOL
325014 6.71 0.04 5.44 7.13 Mol 0.29 -0.10 Bactobolin
326408 8.31 0.04 6.57 8.61 Mol -0.04 -1.03 Rocaglamide Unknown
348115 8.99 0.03 8.64 10.00 Mol 1.10 -0.32 Gilvocarcin V
349156 7.29 0.03 6.70 7.65 Mol -0.22 -0.71 Pancratistatin
354843 6.30 0.05 5.88 7.34 Mol 1.37 -0.24 Albacarcin M
355461 8.40 0.03 7.88 8.96 Mol 1.47 -0.69 B621099K443 Unknown
381837 7.56 0.03 6.97 7.90 Mol -0.07 -0.59 trans-Dihydronarciclasine Unknown
382459 8.00 0.05 6.52 8.00 Mol 0.00 -0.92 1H-Indole-4,7-dione, 5-(1-aziridinyl)-3-(hydroxymethyl)-2-(3-hydroxy-1-propenyl)-1-methyl- Unknown
400978 7.78 0.04 6.61 8.42 Mol 0.16 -0.51 DR-15977 Unknown
400979 7.99 0.05 5.94 8.66 Mol 0.39 -0.49 DR-15978 Unknown
613009 7.17 0.04 6.24 7.65 Mol 1.21 -1.37 Jaspamide
626371 6.00 0.03 6.00 6.69 Mol 0.36 -0.56 Dehydroilludin M Unknown
645318 5.91 0.05 5.72 6.74 Mol -0.31 -0.71 Benzyloxysanguinarine
646616 8.44 0.04 7.94 9.72 Mol 0.15 -1.06 MDP-C857
648060 7.89 0.03 7.01 8.00 Mol 0.52 -0.54 Viridenomycin Unknown
648910 8.67 0.03 8.43 9.67 Mol 0.15 -0.51 Hydramycin
650718 6.21 0.05 5.61 6.75 Mol -0.58 -1.29 Roseophilin, HCl salt
651849 8.00 0.03 6.76 8.28 Mol 0.08 -0.88 .alpha.-D-Glucopyranoside, phenylmethyl 2-acetylamino- 2-deoxy-3-O-[3-[5-[3-(9,10-dihydro-4-nitroacridin- 10-ylamino)propoxy]-1-amino-1,5-dioxo-2-pentylamino]- 3-(3-oxo-2-propylamino)-3-oxo-2-propyl]-
667931 6.30 0.05 5.27 7.09 Mol -0.23 -1.11 6H-1,3-Dioxolo[4,5-g][1]benzopyran-6-amine, 7,8-dihydro- N-(4-methoxyphenyl)-8-(3,4,5-trimethoxyphenyl)-7-methyl- Unknown
670038 10.61 0.03 10.00 11.47 Mol 6.26 -1.47 Cryptophycin B Unknown
670655 8.30 0.04 6.97 8.65 Mol -0.26 -1.32 4a,14a-Epoxy-4,14-[3]hexene[1,5]diynonaphtho[2,3-c] phenanthridine-7,12-dione, 1,2,3,4,13,14-hexahydro- 4,6-dihydroxy-3,3-dimethoxy-1-methyl-, stereoisomer
670851 6.46 0.04 5.91 7.13 Mol -0.43 -1.40 Manzamine A Unknown
676676 6.14 0.04 5.77 7.15 Mol 0.11 -0.56 ARQ monoacetate
681229 7.36 0.05 6.28 7.88 Mol -0.60 -1.54 Boronic acid, [1-[[2-amino-3-(1-naphthalenyl)- 1-oxopropyl]amino]-3-methylbutyl]-, L-(S)-, hydrochloride
681239 8.48 0.03 7.72 8.83 Mol -0.82 -1.91 Bortezomib FDA approved Pr
682506 7.12 0.05 6.52 7.90 Mol 0.28 -1.18 Methanone, 3-(chloromethyl)-2,3-dihydro-6-(dimethylamino)- 1H-indol-1-yl-5,6,7-trimethoxy-1H-indol-2-yl- Unknown
692303 7.47 0.04 6.70 8.00 Mol 1.39 -0.24 2,3-Dihydro-3(R)-[4'hydroxyphenylsulfinyl]brefeldin A
692306 7.32 0.05 6.68 8.00 Mol 1.17 -0.36 2,3-Dihydro-1,2-syn-2-[2'-aminopropylsulfenyl]-brefeldin A
693540 7.87 0.02 7.51 8.00 Mol 0.20 -1.17 Acetamide, N-[2-[[5-amino-1-(chloromethyl)-1,2-dihydro- 3H-benz[e]indol-3-yl]carbonyl]-1H-indol-5-yl]-
693546 8.34 0.05 7.80 9.91 Mol 0.37 -1.25 1H-Benz[e]indol-5-amine, 1-(chloromethyl)-2,3-dihydro-N-methyl- 3-[(5,6,7-trimethoxy-1H-indol-2-yl)carbonyl]-
697539 7.07 0.05 6.53 8.00 Mol 0.01 -1.56 6-Amino-3-chloromethyl-1-((5-(((benzofuran-2-yl)-carbonyl)amino)indol-2-ylcarbonyl)indoline
708495 7.48 0.05 5.89 7.93 Mol -0.08 -0.96 Pancratistatin,1-O-(4-hydroxy-2-oxopentyl)-
712399 7.73 0.05 6.48 8.30 Mol 0.34 0.28 Ambewelamide A
713205 7.63 0.02 7.23 8.00 Mol -0.47 -0.90 Halofuginone Hydrobromide
718798 6.63 0.02 6.47 7.39 Mol 0.42 -0.47 Mensacarcin
730563 6.08 0.05 5.64 6.77 Mol 1.21 -0.45 Miliusane A
730564 6.09 0.04 5.32 6.93 Mol 1.23 -0.44 Miliusane B
744469 6.00 0.05 5.43 6.72 Mol -1.13 -1.56 3-cyano-3,3-diphenylpropyl 4-(3-[(11aS)-7-methoxy-5-oxo-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-8-yl]oxypropyl)-1-piperazinecarbodithioate
745363 7.25 0.04 6.28 7.89 Mol -0.75 -1.35 Chaetocin from Chaetomium minutum
746149 6.07 0.05 5.48 6.68 Mol -0.56 -1.14 N,N'-bis(4-bromo-2-fluorobenzoyl)-L-selenocystine bis(4-methoxyphenacyl) ester hemihydrate

Cluster 6

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
65346 7.06 0.02 6.75 7.55 Mol 0.90 -0.61 Antibiotic from Streptomyces
65423 5.93 0.04 5.61 6.51 Mol 0.89 -0.35 Isopurine, ribosyl- Unknown
72961 6.42 0.04 5.81 7.30 Mol 1.32 -0.36 3H-v-Triazolo[4,5-d]pyrimidine, 7-amino-3-.beta.-D-ribofuranosyl- (8CI) Unknown
99843 7.74 0.04 6.63 8.00 Mol 0.78 -0.69 Antibiotic E 212 Unknown
102816 6.03 0.05 5.10 6.60 Mol 1.12 0.55 Azacitidine FDA approved DNMT
105827 6.73 0.04 6.22 7.71 Mol 0.81 -0.34 SANGIVAMYCIN,-THIO
116282 6.48 0.03 6.04 7.05 Mol 0.62 -0.98 7H-Pyrrolo[2,3-d]pyrimidine-5-carbohydroximic acid, 4-amino-7-.beta.-D-ribofuranosyl-, monohydrochloride (8CI)
122816 6.77 0.03 6.48 7.53 Mol 0.91 -0.31 7H-Pyrrolo[2,3-d]pyrimidin-4(3H)-one, 7-.beta.-D-ribofuranosyl-, oxime
133114 8.17 0.03 7.62 9.00 Mol 0.61 -0.57 Adenosine, 5'-O-(aminosulfonyl)-
143648 7.44 0.05 7.15 8.66 Mol 0.90 -0.61 Sangivamycin Hydrochloride
175630 7.26 0.04 6.62 7.76 Mol 0.59 -0.65 Toyocamycin, 6-amino-
180525 6.59 0.04 6.02 7.25 Mol 0.67 -0.22 Sangivamycin, 6-aminothio-
188491 7.66 0.04 6.63 8.00 Mol 0.43 -0.20 7H-Pyrrolo[2,3-d]pyrimidine-5-carboxamide, 4-amino-6-hydrazino-7-.beta.-D-ribofuranosyl-
352890 8.03 0.03 7.34 8.90 Mol 0.63 -0.61 9-Deazaadenosine Unknown
359079 6.66 0.03 6.24 7.33 Mol 0.83 -0.68 Rebeccamycin
367413 6.36 0.04 5.54 6.72 Mol 0.78 -0.65 1H-Pyrazolo[3,4-d]pyrimidine-3-carboximidamide, 4,5-dihydro-4-oxo-1-.beta.-D-ribofuranosyl-, monohydrochloride
664236 6.81 0.04 6.37 7.76 Mol 0.56 -0.62 Pyrrolo[2,1-f][1,2,4]triazine-4-amine, 7-.beta.-D-ribofuranosyl- Unknown
675865 7.84 0.04 7.02 8.00 Mol 0.54 -0.65 Isothiazolo[4,5-d]pyrimidin-7-amine,3-(.beta.-D-ribofuranosyl)-
750854 7.61 0.03 7.19 8.00 Mol 0.36 -0.73 9H-Purine, 9-[5-O-(aminosulfonyl)-.beta.-D-ribofuranosyl)]-[(2R,3S,4R,5R)-3,4-Dihydroxy-5-(9H-purin-9-yl)tetrahydrofuran-2-yl]methyl sulfamate

Cluster 7

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
618487 8.00 0.04 7.18 9.22 Mol 0.44 -1.33 Staurosporine
638850 7.55 0.05 6.54 8.17 Mol 0.53 -1.24 7-Hydroxystaurosporine Clinical trial STK

Cluster 8

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
185 7.33 0.04 6.66 7.75 Mol 0.19 0.61 .beta.-[2-(3,5-Dimethyl-2-oxocyclohexyl)-2-hydroxyethyl]glutarimide Unknown
1010 6.37 0.03 5.75 6.63 Mol -0.43 -1.10 7-[.ALPHA.-(P-NITROANILINO)BENZYL]-8-QUINOLINOL
3905 6.35 0.04 5.15 6.79 Mol -0.12 -0.37 .alpha.,.alpha.',.alpha.''-Tripyridyl
5013 6.48 0.03 5.82 6.77 Mol -0.17 -0.52 C.I. Solvent Blue 3
5283 6.00 0.05 5.48 6.73 Mol -0.39 5.89 Chlorotriethylstannane
11515 6.15 0.04 5.75 6.51 Mol -0.29 -0.88 Acranil
12454 6.27 0.04 5.60 6.63 Mol -0.07 -0.47 C.I. Basic Yellow 7
13002 5.99 0.03 5.76 6.53 Mol -0.13 -0.56 Acridine, 9-(p-dimethylaminoanilino)-
13006 6.22 0.04 5.30 6.67 Mol -0.09 -0.86 Ethanol, 2-[(2-[(2-methoxy-9-acridinyl)amino]ethyl)amino]-, dihydrochloride
15013 6.68 0.05 5.74 7.16 Mol -0.11 -0.36 ANQI
22323 6.92 0.03 6.57 7.77 Mol -0.40 5.28 Chlorid tri-N-butylcinicity (CZECH)
32944 7.64 0.03 6.40 8.03 Mol -0.23 -0.89 Emetan-6'-ol, 7',10,11-trimethoxy-, dihydrochloride (9CI) Unknown
33409 6.38 0.04 5.59 6.75 Mol -0.29 -0.56 Colchinol, N-acetyliodo-, methyl ether
33461 6.23 0.04 5.68 6.71 Mol -0.15 -0.46 Aniline, 4,4'-imidocarbonylbis[N,N-diethyl-, monohydrochloride (8CI)
33669 7.69 0.04 6.49 8.46 Mol -0.35 -0.91 Emetine Hydrochloride Unknown
37187 6.45 0.04 5.47 6.97 Mol -0.31 -0.52 Acco Naf-Sol AS-KB
37608 6.41 0.04 5.45 6.76 Mol -0.20 -0.49 C.I. Azoic Coupling Component 27
41390 7.36 0.03 6.80 7.77 Mol -0.05 -0.86 ANTINEOPLASTIC-41390
43675 7.57 0.04 6.56 7.91 Mol -0.37 5.27 Brestanol
47147 8.00 0.04 6.60 8.00 Mol -0.65 -1.28 Prodigiosin
47731 6.60 0.04 5.82 7.32 Mol -0.27 -0.40 Aniline, p-[[p-(dimethylamino)phenyl][4-(methylimino)-2,5-cyclohexadien-1-ylidene]methyl]-N,N-dimethyl-, monohydrochloride (8CI)
60387 7.64 0.04 6.91 8.00 Mol -0.18 -0.58 Dibenzo[f,h]pyrrolo[1,2-b]isoquinoline, 9,11,12,13,13a,14-hexahydro-2,3,5,6-tetramethoxy-, (R)- (9CI) Unknown
68088 6.37 0.04 5.43 6.74 Mol -0.60 -1.00 Guanidine, [(p-fluoro-.alpha.-phenylbenzylidene)amino]-, monohydrochloride
69603 6.35 0.04 5.58 7.28 Mol -0.27 -0.87 Quinoline, 4-(2,5-dimethoxystyryl)-
71795 6.11 0.04 5.63 6.86 Mol 0.28 -0.71 Ellipticine
76387 7.44 0.05 6.42 8.31 Mol -0.21 -0.57 Dibenzo[f,h]pyrrolo[1,2-b]isoquinoline, 9,11,12,13,13a,14-hexahydro-2,3,6,7-tetramethoxy-, (S)- (9CI)
76557 7.64 0.03 7.00 8.00 Mol -0.39 1.81 Tin, bis(triphenyl- ) ethylenebis(dithiocarbamate)
76712 7.67 0.02 7.26 8.00 Mol 0.28 -0.59 Anisomycin Unknown
83459 6.25 0.05 5.20 6.59 Mol -0.56 -0.87 Indole-2,3-dione, 3-(4,4-dimethyl-3-thiosemicarbazone)
92904 7.31 0.03 6.80 7.84 Mol -0.02 -0.66 ANTINEOPLASTIC-92904
100055 7.26 0.04 6.31 8.00 Mol -0.04 -0.79 Tylophorinine Unknown
102980 6.86 0.02 6.66 7.25 Mol -0.39 2.45 (2,4-Dichlorophenoxy)tributylstannane
103837 6.42 0.03 5.72 6.71 Mol -0.42 0.48 .beta.-Resorcylaldehyde, 1,4-phthalazinediyldihydrazone
118028 7.88 0.03 6.95 8.00 Mol -0.21 1.29 Phenazastanine, 5,10-dihydro-5,10,10-trimethyl-
129414 7.51 0.04 6.50 8.00 Mol -0.23 -0.98 (.+-.)-2,3-Dehydroemetine dihydrochloride
141819 6.73 0.02 6.30 7.04 Mol -0.22 2.70 Bromotriphenyllead(IV)
143103 6.35 0.05 5.44 7.21 Mol -0.40 -1.13 Methanesulfonamide, N-[4-[(3-methoxy-9-acridinyl)amino]phenyl]-, monohydrochloride (9CI) (MF1)
145669 7.44 0.05 6.34 8.00 Mol -0.45 -0.74 4(1H)-Quinazolinone, 2,3-dihydro-2-(1-naphthalenyl)- (9CI) Unknown
146109 6.74 0.04 6.05 7.71 Mol -0.20 -0.65 Pseudourea, 2-[(10-methyl-9-anthryl)methyl]-2-thio-, monohydrochloride
165714 6.29 0.04 5.69 7.42 Mol -0.20 -0.62 9-Acridinamine, N-(4-ethoxyphenyl)-, monohydrochloride
168597 7.52 0.04 6.89 8.37 Mol -0.40 5.28 Plumbane, chlorotributyl- Unknown
178264 6.68 0.05 5.67 7.36 Mol -0.19 -0.06 Fluopsin N Unknown
178296 6.61 0.04 5.67 7.23 Mol -0.32 -0.47 Atenase
205105 6.50 0.05 5.56 7.40 Mol -0.49 -0.72 Hydrazinecarbothioamide, 2-[(5-amino-1-isoquinolinyl)methylene]- (9CI)
220589 6.68 0.04 5.94 7.45 Mol -0.55 -0.73 Ethanol, 2,2'-[[2-(5-nitro-2-furanyl)-4-quinazolinyl]imino]bis- (9CI)
242557 6.40 0.04 5.90 7.19 Mol -0.25 -0.24 (3,5-Di-t-butyl-4-hydroxybenzylidene)malononitrile
247561 8.50 0.04 7.80 9.00 Mol -0.29 -0.82 C 283
263434 7.14 0.05 6.23 7.74 Mol -0.20 -0.82 N,N'-Bis(3-methoxy-9-acridinyl)-1,8-octanediamine
265959 6.49 0.04 5.14 7.27 Mol -0.28 -0.71 6H-Cyclopenta[c][1,8]phenanthrolin-6-one, 5,7,8,9-tetrahydro-
295505 8.00 0.02 7.20 8.00 Mol -0.33 -0.91 C 829
299863 6.52 0.02 6.15 7.07 Mol -0.14 -0.33 Benzenemethanol, 4-(1,1-dimethylethyl)-.alpha.,.alpha.-bis[4-(1,1-dimethylethyl)-2,6-dimethoxyphenyl]-2,6-dimethoxy-
306365 6.71 0.04 5.73 7.43 Mol -0.28 -0.76 Quino[8,7-h]quinoline-1,7-diamine, N,N'-bis[3-(dimethylamino)propyl]-3,9-dimethyl-, tetrahydrochloride
335307 6.38 0.04 5.48 6.89 Mol -0.38 -0.08 Carbamic acid, [5-(cyclopropylcarbonyl)-1H-benzimidazol-2-yl]-, methyl ester (9CI)
349155 6.50 0.04 6.00 7.31 Mol 0.03 -0.47 B844009K069
370589 6.42 0.04 5.55 6.65 Mol -0.56 -1.40 2-Pyridinecarbaldehyde (5-methyl-5H-[1,2,4]triazino[5,6-b]indol-3-yl)hydrazone
527347 6.35 0.03 5.63 6.59 Mol -0.62 -0.56 Picolinaldehyde, 2-quinolylhydrazone (8CI)
617969 6.05 0.04 5.32 6.65 Mol -0.21 -0.95 1,4-Acridinedicarboxamide, N,N'-bis[2-(dimethylamino) ethyl]-, trihydrochloride Unknown
624548 7.47 0.03 7.00 8.10 Mol 0.07 -1.24 Benzamide, N-[[[4-[(5-bromo-2-pyrimidinyl)oxy]-3- chlorophenyl]amino]carbonyl]-2-nitro-
628585 7.78 0.02 7.29 8.00 Mol -0.36 1.62 ANTINEOPLASTIC-628585
633555 6.63 0.04 6.00 7.00 Mol 0.11 -0.34 Acylfulvene
645804 8.31 0.04 8.00 9.33 Mol -0.31 -0.82 9-Acridineamine, N-[5-(dimethylamino)pentyl]- 1-nitro-, dihydrochloride Unknown
645805 8.22 0.04 7.80 9.35 Mol -0.35 -0.83 1,3-Propanediamine, N-methyl-N'-(1-nitro-9-acridinyl)-,dihydrochloride Unknown
645806 8.32 0.04 6.89 8.97 Mol -0.18 -0.70 9-Acridineamine, N-[2-[bis(2-hydroxyethyl)amino]ethyl]- 1-nitro-, dihydrochloride
645807 7.95 0.05 7.00 8.87 Mol -0.25 -0.67 ANTINEOPLASTIC-645807 Unknown
649890 7.35 0.03 6.51 7.74 Mol 0.34 -0.67 Alvocidib Hydrochloride Clinical trial STK
650395 8.51 0.03 7.71 9.02 Mol -0.11 -0.65 Tyloindicine H Unknown
650396 8.34 0.02 7.68 8.76 Mol -0.26 -0.95 Tyloindicine I
664215 6.54 0.05 5.92 7.40 Mol 0.38 0.05 Chloro-methoxy-tetrangulol Unknown
668360 7.67 0.05 6.43 8.00 Mol -0.47 -0.63 Ethanone, 1,1'-[(1,1'-biphenyl)-2,2'-diyl] bis[2-(triphenylphosphoranylidene)- Unknown
671196 6.41 0.03 6.08 7.22 Mol 0.29 -0.22 Elsinochrome B Unknown
671197 6.09 0.03 5.61 6.62 Mol 0.34 -0.34 Elsinochrome C Unknown
673792 8.03 0.04 6.32 8.66 Mol -0.15 -0.84 9-Acridinamine, N-[2-[(2-hydroxyethyl)amino]ethyl]-1-nitro-
673793 7.56 0.05 6.16 8.00 Mol -0.17 -0.83 9-Acridinamine, N-[2-[bis(2-hydroxyethyl)amino]ethyl]-7-methoxy-1-nitro- Unknown
674067 5.85 0.05 5.70 6.75 Mol -0.55 -1.22 Bicyclo[2.2.1]heptan-2-amine, N,N'-(1,3-phenylene)bis[3-(5-methoxy-1H-indol-3-yl)-, stereoisomer Unknown
674104 6.13 0.04 5.57 6.64 Mol -0.68 -1.20 2-Acetylimidazo[4,5-b]pyridin 4 p-nitrophenyl 3 thio-semicarbazone
674350 6.74 0.04 6.00 7.69 Mol -0.39 -0.52 3,6-Dimethylthio-dihydrotetrazine
674351 6.58 0.03 6.01 7.24 Mol 0.10 -0.41 1,4-Dimethoxy-7-bromo-5H-benzocycloheptene
674699 7.77 0.05 6.04 8.00 Mol -0.26 -0.94 9-[3-[N-(2-N,N-Dimethylamino)ethyl]aminopropyl]amino- 1-nitroacridine.3HCl Unknown
678913 6.13 0.04 5.52 6.84 Mol -0.28 -0.81 4-Acridinecarboxamide, 1-chloro-N-[2-(dimethylamino) ethyl]-, dihydrochloride Unknown
679748 6.66 0.05 5.72 7.70 Mol 0.17 -0.26 [1,1'-Binaphthalene]-3,3',4,4'-tetrone, 2,2',6,6'-tetramethyl- Unknown
695589 6.75 0.05 5.74 7.79 Mol 0.20 -1.13 6-Amino-3-chlormethyl-1-[(5-methoxyindol-2-yl)-carbonyl] indoline
702015 6.48 0.04 5.78 6.89 Mol -0.60 -1.47 1H-Indole-2-carboxylic acid, 2,3,5,11a-tetrahydro-7-methoxy-5-oxo- 1H-pyrrolo[2,1-c][1,4]benzodiazepin-8-yl ester, (11aS)-
706126 6.84 0.03 6.36 7.38 Mol 0.14 -0.64 (2R,3S,4S)-3,4-O-Diacetyl-3,4-dihydroxy-2-(p-methoxybenzyl)-pyrrolidine hydrochloride
708472 6.11 0.03 5.63 6.51 Mol 0.63 -0.86 Beauvericin (8CI, 9CI)
711945 8.00 0.03 7.08 8.00 Mol 0.20 -0.87 Acetamide, N,N'-[1,5-dioxo-1,5-pentanediyldi[1-(chloromethyl)- 2,3-dihydro-5-hydroxy-1H-benz[e]indole-3,7-diyl]]bis-
711948 8.00 0.04 6.17 8.00 Mol 0.20 -0.87 Acetamide, N,N'-[1,8-dioxo-1,8-octanediyldi[1-(chloromethyl)- 2,3-dihydro-5-hydroxy-1H-benz[e]indole-3,7-diyl]]bis-
716802 7.55 0.02 6.84 8.00 Mol -0.01 -0.71 Dibenzo[f,h]pyrrolo[1,2-b]isoquinolin-14-ol, 9,11,12,13,13a,14-hexahydro-2,3,6,7-tetramethoxy-, (13aS-trans)-
740043 6.04 0.04 5.43 6.57 Mol -0.71 -1.37 7-bromo-indirubin with water-solubilizing extension on position 3'
740383 6.63 0.05 5.78 7.24 Mol -0.47 -0.95 3,7-di(trifluoromethyl)-2-(thien-2-ylcarbonyl)quioxaline 1,4-dioxide
741425 6.05 0.05 5.47 6.76 Mol -0.36 -0.76 3,7-di(trifluoromethyl)-2-naftoylquioxaline 1,4-dioxide
742293 6.10 0.05 5.55 7.11 Mol -0.65 -1.47 (11aS)-8-4-[4-(1,3-benzothiazol-2-yl)phenoxy]butoxy-7-methoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
742296 6.91 0.05 6.03 7.88 Mol -0.64 -1.44 (11aS)-8-(5-[4-(1,3-benzothiazol-2-yl)-2-methoxyphenoxy]pentyloxy)-7-methoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
742543 6.58 0.05 5.72 7.21 Mol -0.05 -0.72 Naphth[1',2':4,5]imidazo[1,2-a]pyridine-5,6-dione, 9-methyl-
743121 7.58 0.04 6.43 7.98 Mol -0.69 -1.62 (11aS)-7-methoxy-8-3-[4-(4-quinazolinyl)piperazino]propoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepine-5-one
743122 6.62 0.03 5.77 7.24 Mol -1.08 -1.74 N1-[4-chloro-2-(2-chlorobenzyl)phenyl]-2-[4-(5-[-(11aS)-7-methoxy-5-oxo-2,3,5,11a,-tetrahydro-1H-benzo[e]pyrrolo[1,2-a] [1,4]diazepin-8-yl]oxybutyl)piperazino]acetamide
743134 6.59 0.04 5.98 7.35 Mol -1.09 -1.75 N1-[4-chloro-2-(2-cholrobenzoyl)phenyl]-2-[4-(6-[(11aS)-7-methoxy-5-oxo-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-8-yl]oxyhexyl)piperazino]acetamide
743135 7.60 0.04 6.42 8.00 Mol -0.74 -1.59 (11aS)-7-methoxy-8-(5-[4-(4-quinazolinyl)piperazino]pentyloxy)-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
744023 7.38 0.05 6.46 7.73 Mol -0.51 -1.25 (11aS)-8-(3-{4-[(E)-3-(2-hydroxyphenyl)-3-oxo-1-propenyl]-2-methoxyphenoxy}propoxy)-7-methoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
744327 7.54 0.04 6.41 8.00 Mol -0.76 -1.62 7-methoxy-8-[(5-2-methoxy-4-[(E)-3-(2,4-dimethyl-3-quinolyl)-3-oxo-1-propenyl]phenoxypentyl)oxy]-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
744332 6.59 0.03 5.71 6.86 Mol -0.64 -1.36 (11aS)-7-methoxy-8-6-[4-(2-methyl-4-oxo-3,4-dihydro-3-quinazolinyl)phenoxy]pentyloxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
744336 6.56 0.04 5.55 6.92 Mol -0.50 -1.57 (11aS)-7-methoxy-8-(4-2-methoxy-4-[5-(3,4,5-trimethoxyphenyl)-4,5-dihydro-3-isoxazolyl]phenoxybutoxy)-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
744989 6.40 0.05 5.52 6.73 Mol -0.72 -1.61 7-methoxy-8-[(5-2-methoxy-4-[(E)-3-(2,4-dimethyl-3-quinolyl)-3-oxo-1-propenyl]phenoxybutyl)oxy]-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
745355 6.45 0.04 5.79 7.16 Mol -0.53 -1.42 7-methoxy-8-(4-2-methoxy-4-[(10-oxo-9,10-dihydro-9-nthracenyliden)methyl]
745357 6.66 0.04 5.76 6.77 Mol -0.14 -0.61 Bispurines
749673 6.25 0.05 5.37 7.17 Mol -0.71 -1.29 N1-(2,15-dioxo-1-(pyren-1-yl)-6,9,12-trioxa-3,16-diazanonadecan-19-yl)-N1-methyl-N3-(2-(naphthalen-2-yl)quinolin-4-yl)propane-1,3-diaminium bromide
750213 7.04 0.05 5.82 7.55 Mol -0.08 -0.66 4-(2-hydroxyethyl)-10-phenyl-3,4,6,7,8,10-hexahydro-1H-cyclopenta[g]furo[3,4-b]quinolin-1-one
751249 7.98 0.02 7.15 8.00 Mol -0.76 -1.45 BEZ235 Clinical trial STK
751286 6.40 0.03 5.29 6.61 Mol -0.55 -1.46 5-Methyl-3-(2-(pyridin-2ylmethyl)hydrazinyl)-5H-[1,2,4]triazino[5,6-b]indole, trihydrochloride
751342 6.80 0.04 6.17 7.50 Mol -0.33 -1.25 12H-Benzo[g]pyrido[2,1-b]quinazoline-4-carboxamide, N-[2(dimethylamino)ethyl]-12-oxo

In [151]:
In [149]: 
nsc_info.head()
Out[149]:
Drug name FDA Status Mechanism of Action
NSC #
1 p-Benzoquinone, 2-methyl- (8CI) NaN NaN
1 p-Benzoquinone, 2-methyl- (8CI) NaN NaN
1 p-Benzoquinone, 2-methyl- (8CI) NaN NaN
17 4-AMINO-3-PENTADECYLPHENOL NaN NaN
17 4-AMINO-3-PENTADECYLPHENOL NaN NaN
In []: